Agricultural harvesters are used to harvest the plants from a field. Processing operations take place in the harvester, so as to handle the crops for the purpose of a later further processing. Thus, the crops are chopped in a field chopper and threshed in a combine thresher, separated, and cleaned. In these processing operations, various work parameters of the harvester are set; with a field chopper, for example, the cutting length and, perhaps, an effective intensity of a conditioning device and with a combine harvester, the threshing drum speed, the threshing slit, the speed of the cleaning blower, and the sieve opening, and with all harvesters, the rate of advance that determines the individual throughput.
For most combine harvesters, basic settings for the work elements such as the threshing element, the residual grain separation, and the cleaning device are proposed as empirical values by the manufacturer. On the basis of the great variation of actual characteristics of the crops, these proposals can only be initial approximations. The only thing the operator still needs to do is to optimize the settings, depending on the available specifications (for example, crops with low losses or in the shortest possible time) and crop conditions, so as to be able to utilize the full performance capacity of the machine. That can take place in a purely manual manner according to its own strategy in a dialogue operation with assistance systems (see EP 2 165 591 A1), or automatically with an automatic adjustment system (EP 2 401 904 A2). A basic problem remains in that the dividing, separating, and cleaning operations in a combine harvester are very complex and their results can be monitored only by a few sensors. Even with so-called anticipatory sensors, no absolute relationship is yet recognizable, initially, to the partial operations in the combine harvester and its results. For this reason, various methods have been proposed in the past for the mathematical modeling of the processes, on whose basis a setting of the function elements can take place (neural networks, fuzzy controllers, regression models, and so forth).
All these models, however, must first be also coordinated with the individual harvesting conditions and goal formulations. They require a certain training phase. Furthermore, the sensors used in these processes must also first be calibrated so as to be able to provide reliable information. Proceeding from the settings found in the training phase, these systems can then compensate for variations in the harvesting conditions to a certain extent by adapting to the machine setting and the traveling speed. If the deviations are excessively large, these systems must also be recoordinated and the sensors must be recalibrated. These training phases and calibration require a certain time period during which the prevailing boundary conditions should be maintained as constant as possible.
The disadvantage exists, moreover, that feedback sensors interact with crops in the harvester, and for that reason, with changes in the characteristics of the gathered crops, reactions come much too late. In the state of the art, therefore, different procedures are described in which the attempt is made so that with an adjustment of the work parameters of the harvester, the characteristics of the crops to be harvested in each case are taken into consideration, in an anticipatory manner, by an automatic control.
In this respect, sensors are used, on the one hand, which, in an anticipatory manner, have a view of the crops from the harvester, so as to determine their characteristics (for example, density, maturity), and so as to change, with the aid of the determined characteristics, work parameters and settings of the harvester, such as the rate of advance (DE 101 30 665 A1).
On the other hand, methods are described in which an electronic map with field characteristics and/or operating data of the harvester is first set up, so as to recall the map data during the harvest in a georeferenced manner and to use them to set up work parameters of the harvester to be adjusted automatically.
DE 44 31 824 C1, for example, proposes that, in a first harvesting operation, the yield data for the grain and straw throughput, grain losses, and adjusted theoretical values of the operating parameters be stored in a map, in a georeferenced manner. In the next harvesting operation, the data from the map are recalled, in an anticipatory and georeferenced manner, so as to derive therefrom the individual working parameters of the harvester. The possibility of inserting a subordinate control loop thereby exists, which is based on a so-called reverse control action for the traveling speed, in which the individual throughputs of the combine harvester are locally recorded and used for the determination of the traveling speed, so as to obtain a constant throughput performance and/or constant settings of the work elements of the combine harvester.
DE 10 2005 000 770 B3 describes a procedure for the automatic control of a combine harvester, in which a theoretical map, which is used for the fundamental control of the combine harvester, is to be set up on the basis of georeferenced data obtained during the biomass development. During the harvesting operation, a regulation of the rate of advance and the setting of the work parameters of the combine harvester take place on the basis of the theoretical map so as to attain an acceptable threshing quality and losses.
With the anticipatory sensors, it has proved problematic to record sufficiently exact data at a distance that extends sufficiently far in front in order to take into account the reaction times of the actuators for the purpose of a prompt change of the work parameters of the combine harvester. Suitable sensors are thus relatively cumbersome and expensive. With the known systems based on georeferenced sensors, there is the problem that the actual harvesting characteristics are not always exactly in agreement with the characteristics predicted from the map, which can lead to inappropriate work parameters for the harvester. The subordinate control with a rear control action in accordance with DE 44 31 824 C1 reduces this problem, however, but there still remain inaccuracies in the data derived only from the map that make a local optimization of work parameters for the harvester and/or a calibration of feedback sensors, in particular the loss sensors, appear to be useful, but which is not provided for in the state of the art.
The goal of the invention under consideration is then seen as providing a system and a method for the automatic setting of processing parameters for an agricultural machine that does not have the aforementioned disadvantages or has them only to a lesser extent.